Abstract

It is conjectured that the size of a hedge fund has some impact on its return. In this paper, we investigate the relationship between them and apply the results to construct an investment model. We first implement a learning algorithm to construct a piecewise linear regression model which shows that a fund's AUM (Asset Under Management) has different effects in different situations on its return. Then, with consideration of the various scenarios, we propose a robust optimization model to maximize the expected profit. Finally, we present the computational results that illustrate the strength of our two-stage procedure.